TST: catch/suppress test warnings (pandas-dev#41346)

Author: jbrockmendel

pandas/tests/generic/test_finalize.py

@@ -226,7 +226,10 @@
     ),
     pytest.param(
         (pd.DataFrame, frame_mi_data, operator.methodcaller("count", level="A")),
-        marks=not_implemented_mark,
+        marks=[
+            not_implemented_mark,
+            pytest.mark.filterwarnings("ignore:Using the level keyword:FutureWarning"),
+        ],
     ),
     pytest.param(
         (pd.DataFrame, frame_data, operator.methodcaller("nunique")),

pandas/tests/io/__init__.py

@@ -5,6 +5,12 @@
     pytest.mark.filterwarnings(
         "ignore:PY_SSIZE_T_CLEAN will be required.*:DeprecationWarning"
     ),
+    pytest.mark.filterwarnings(
+        "ignore:Block.is_categorical is deprecated:DeprecationWarning"
+    ),
+    pytest.mark.filterwarnings(
+        r"ignore:`np\.bool` is a deprecated alias:DeprecationWarning"
+    ),
     # xlrd
     pytest.mark.filterwarnings(
         "ignore:This method will be removed in future versions:DeprecationWarning"

pandas/tests/io/formats/style/test_highlight.py

@@ -5,6 +5,7 @@
     DataFrame,
     IndexSlice,
 )
+import pandas._testing as tm
 
 pytest.importorskip("jinja2")
 
@@ -54,7 +55,9 @@ def test_highlight_minmax_basic(df, f):
     }
     if f == "highlight_min":
         df = -df
-    result = getattr(df.style, f)(axis=1, color="red")._compute().ctx
+    with tm.assert_produces_warning(RuntimeWarning):
+        # All-NaN slice encountered
+        result = getattr(df.style, f)(axis=1, color="red")._compute().ctx
     assert result == expected
 
 

pandas/tests/io/pytables/__init__.py

@@ -9,4 +9,7 @@
     pytest.mark.filterwarnings(
         r"ignore:`np\.object` is a deprecated alias:DeprecationWarning"
     ),
+    pytest.mark.filterwarnings(
+        r"ignore:`np\.bool` is a deprecated alias:DeprecationWarning"
+    ),
 ]

pandas/tests/io/pytables/test_categorical.py

@@ -216,7 +216,7 @@ def test_convert_value(setup_path, where: str, df: DataFrame, expected: DataFram
     max_widths = {"col": 1}
     categorical_values = sorted(df.col.unique())
     expected.col = expected.col.astype("category")
-    expected.col.cat.set_categories(categorical_values, inplace=True)
+    expected.col = expected.col.cat.set_categories(categorical_values)
 
     with ensure_clean_path(setup_path) as path:
         df.to_hdf(path, "df", format="table", min_itemsize=max_widths)

pandas/tests/io/test_parquet.py

@@ -3,7 +3,10 @@
 from io import BytesIO
 import os
 import pathlib
-from warnings import catch_warnings
+from warnings import (
+    catch_warnings,
+    filterwarnings,
+)
 
 import numpy as np
 import pytest
@@ -36,7 +39,10 @@
     _HAVE_PYARROW = False
 
 try:
-    import fastparquet
+    with catch_warnings():
+        # `np.bool` is a deprecated alias...
+        filterwarnings("ignore", "`np.bool`", category=DeprecationWarning)
+        import fastparquet
 
     _HAVE_FASTPARQUET = True
 except ImportError: